Egret

Tools for building power systems optimization problems

https://github.com/grid-parity-exchange/Egret

Science Score: 49.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 1 DOI reference(s) in README
  • Academic publication links
  • Committers with academic emails
    3 of 34 committers (8.8%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (18.6%) to scientific vocabulary

Keywords

energy-system milp minlp nlp optimization power powerflow python snl-applications snl-science-libs

Keywords from Contributors

mathematical-programming modeling-language nonlinear-programming idaesplus
Last synced: 6 months ago · JSON representation

Repository

Tools for building power systems optimization problems

Basic Info
  • Host: GitHub
  • Owner: grid-parity-exchange
  • License: other
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 30.2 MB
Statistics
  • Stars: 142
  • Watchers: 13
  • Forks: 59
  • Open Issues: 54
  • Releases: 6
Topics
energy-system milp minlp nlp optimization power powerflow python snl-applications snl-science-libs
Created about 7 years ago · Last pushed 8 months ago
Metadata Files
Readme Contributing License

README.md

EGRET GitHub CI

EGRET Overview

EGRET is a Python-based package for electrical grid optimization based on the Pyomo optimization modeling language. EGRET is designed to be friendly for performing high-level analysis (e.g., as an engine for solving different optimization formulations), while also providing flexibility for researchers to rapidly explore new optimization formulations.

Major features: * Solution of Unit-Commitment problems * Solution of Economic Dispatch (optimal power flow) problems (e.g., DCOPF, ACOPF) * Library of different problem formulations and approximations * Generic handling of data across model formulations * Declarative model representation to support formulation development

EGRET is available under the BSD License (see LICENSE.txt)

Primary Contributors

Ben Knueven

  • Unit commitment
  • ModelData
  • DCOPF
  • PTDF

Anya Castillo

  • ModelData
  • DCOPF
  • ACOPF
  • AC relaxations
  • PTDF

Carl Laird

  • ModelData
  • DCOPF
  • ACOPF
  • AC relaxations

Michael Bynum

  • DCOPF
  • ACOPF
  • AC relaxations

Darryl Melander

  • Unit commitment

JP Watson

  • Unit commitment
  • AC relaxations

Getting Started

Installation

  • EGRET is a Python package and therefore requires a Python installation. We recommend using Anaconda with the latest Python (https://www.anaconda.com/distribution/).
  • These installation instructions assume that you have a recent version of Pyomo installed, in addition to a suite of relevant solvers (see www.pyomo.org for additional details).
  • Download (or clone) EGRET from this GitHub site.
  • From the main EGRET folder (i.e., the folder containing setup.py), use a terminal (or the Anaconda prompt for Windows users) to run setup.py to install EGRET into your Python installation - as follows:

    pip install -e .

Requirements

  • Python 3.7 or later
  • Pyomo version 6.4.0 or later
  • pytest
  • Optimization solvers for Pyomo - specific requirements depends on the models being solved. EGRET is tested with Gurobi or CPLEX for MIP-based problems (e.g., unit commitment) and Ipopt (with HSL linear solvers) for NLP problems.

We additionally recommend that EGRET users install the open source CBC MIP solver. The specific mechanics of installing CBC are platform-specific. When using Anaconda on Linux and Mac platforms, this can be accomplished simply by:

conda install -c conda-forge coincbc

The COIN-OR organization - who developers CBC - also provides pre-built binaries for a full range of platforms on https://bintray.com/coin-or/download.

Testing the Installation

To test the functionality of the unit commitment aspects of EGRET, execute the following command from the EGRET models/tests sub-directory:

pytest test_unit_commitment.py

If EGRET can find a commerical MIP solver on your system via Pyomo, EGRET will execute a large test suite including solving several MIPs to optimality. If EGRET can only find an open-source solver, it will execute a more limited test suite which mostly relies on solving LP relaxations. Example output is below.

``` =================================== test session starts ================================== platform darwin -- Python 3.7.7, pytest-5.4.2, py-1.8.1, pluggy-0.13.0 rootdir: /home/some-user/egret collected 21 items

testunitcommitment.py s.................... [100%]

========================= 20 passed, 1 skipped in 641.80 seconds ========================= ```

How to Cite EGRET in Your Research

If you are using the unit commitment functionality of EGRET, please cite the following paper:

On Mixed-Integer Programming Formulations for the Unit Commitment Problem Bernard Knueven, James Ostrowski, and Jean-Paul Watson. INFORMS Journal on Computing (Ahead of Print) https://pubsonline.informs.org/doi/10.1287/ijoc.2019.0944

Owner

  • Name: Grid Parity Exchange
  • Login: grid-parity-exchange
  • Kind: organization

GitHub Events

Total
  • Issues event: 1
  • Watch event: 10
  • Delete event: 1
  • Issue comment event: 5
  • Push event: 9
  • Pull request review comment event: 6
  • Pull request review event: 7
  • Pull request event: 7
  • Fork event: 6
  • Create event: 1
Last Year
  • Issues event: 1
  • Watch event: 10
  • Delete event: 1
  • Issue comment event: 5
  • Push event: 9
  • Pull request review comment event: 6
  • Pull request review event: 7
  • Pull request event: 7
  • Fork event: 6
  • Create event: 1

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 779
  • Total Committers: 34
  • Avg Commits per committer: 22.912
  • Development Distribution Score (DDS): 0.692
Past Year
  • Commits: 19
  • Committers: 3
  • Avg Commits per committer: 6.333
  • Development Distribution Score (DDS): 0.579
Top Committers
Name Email Commits
Bernard Knueven B****n@n****v 240
bknueven b****e@s****v 230
Michael Bynum m****m 69
Castillo a****i@s****v 49
Knueven b****e@s****v 41
Laird c****d 30
Darryl Melander d****n@s****v 27
Ricky Concepcion r****p@s****v 16
rconcep r****p@s****v 12
jwatsonnm j****n@s****v 10
David L Woodruff D****f 7
Min W. Priest (they/them) b****r@g****m 7
Watson w****1@m****v 5
John Siirola j****a 4
Austin Short a****t@s****v 4
Knueven b****e@r****v 3
Knueven b****e@r****v 3
Knueven b****e@s****l 2
Knueven b****e@r****v 2
Knueven b****e@r****v 2
Edna Soraya Rawlings e****i@s****v 2
jeanpaulwatson 6****n 2
Watson w****1@m****v 1
Knueven b****e@r****v 1
Knueven b****e@r****v 1
Watson w****1@m****v 1
Knueven b****e@r****v 1
Knueven b****e@r****v 1
Dillard Robertson d****d@r****m 1
Bernard Knueven b****n@e****v 1
and 4 more...

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 87
  • Total pull requests: 242
  • Average time to close issues: about 1 month
  • Average time to close pull requests: 7 days
  • Total issue authors: 23
  • Total pull request authors: 15
  • Average comments per issue: 0.98
  • Average comments per pull request: 0.62
  • Merged pull requests: 218
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 4
  • Pull requests: 9
  • Average time to close issues: N/A
  • Average time to close pull requests: 6 days
  • Issue authors: 2
  • Pull request authors: 3
  • Average comments per issue: 0.0
  • Average comments per pull request: 1.11
  • Merged pull requests: 7
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • bknueven (28)
  • michaelbynum (13)
  • jeanpaulwatson (10)
  • DLWoodruff (8)
  • carldlaird (5)
  • MajidSKhoshghalb (2)
  • lbianchi-lbl (2)
  • jwatsonnm (2)
  • whart222 (2)
  • goghino (2)
  • etoenges (1)
  • anyacastillo (1)
  • esrawli (1)
  • SimonRubenDrauz (1)
  • darrylmelander (1)
Pull Request Authors
  • bknueven (149)
  • michaelbynum (26)
  • anyacastillo (15)
  • darrylmelander (15)
  • jeanpaulwatson (10)
  • rconcep (7)
  • carldlaird (5)
  • jwatsonnm (4)
  • bwpriest (4)
  • DLWoodruff (2)
  • HunterTracer (1)
  • austinshort (1)
  • kdheepak (1)
  • barguel (1)
  • jsiirola (1)
Top Labels
Issue Labels
enhancement (1)
Pull Request Labels
invalid (2) bug (1) enhancement (1)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 11,664 last-month
  • Total dependent packages: 1
  • Total dependent repositories: 4
  • Total versions: 6
  • Total maintainers: 1
pypi.org: gridx-egret

EGRET: Electrical Grid Research and Engineering Tools.

  • Versions: 6
  • Dependent Packages: 1
  • Dependent Repositories: 4
  • Downloads: 11,664 Last month
Rankings
Downloads: 3.1%
Dependent packages count: 3.2%
Average: 5.4%
Forks count: 5.9%
Stargazers count: 6.9%
Dependent repos count: 7.6%
Maintainers (1)
Last synced: 6 months ago

Dependencies

.github/workflows/egret.yml actions
  • actions/checkout v2 composite
  • conda-incubator/setup-miniconda v2 composite
.github/workflows/prescient.yml actions
  • actions/checkout v2 composite
  • conda-incubator/setup-miniconda v2 composite
.github/workflows/publish-to-test-pypi.yml actions
  • actions/checkout main composite
  • actions/setup-python v1 composite
  • pypa/gh-action-pypi-publish release/v1 composite
setup.py pypi